MétaCan
Menu
Back to cohort
Record W4396708507 · doi:10.59957/jctm.v59.i3.2024.18

SYNTHESIS OF COPOLYMERS FOR PROTECTIVE COATINGS

2024· article· en· W4396708507 on OpenAlex
V. V. Merkulov, G. A. Ulyeva, Gulzhainat Akhmetova, Andrey Volokitin

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Chemical Technology and Metallurgy · 2024
Typearticle
Languageen
FieldMaterials Science
TopicMaterial Properties and Applications
Canadian institutionsArcelorMittal (Canada)
Fundersnot available
KeywordsCopolymerMaterials sciencePolymer scienceComposite materialPolymer

Abstract

fetched live from OpenAlex

Copolymers were obtained in this work and the methodology for their synthesis was worked out. Various fillers were selected for the polymer coating. Resulting copolymers have good adhesion required for composite protective coatings. An experiment was conducted to determine the corrosion resistance of metals coated with copolymers when exposed to aggressive environments, as well as to determine the hardness and thickness of the polymer coatings obtained. It was found that the polymer coating filled with bronze powder, despite the small thickness of 43.4 μm, hasthe best adhesion and corrosion properties, as well as having the highest hardness values of 80.5 HB. Such physical and mechanical properties of polymer coatings allow them to be used as protective coatings for metal products working under the influence of aggressive media.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.159

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.251
Teacher spread0.239 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it